PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
SELECT DISTINCT ?person ?personLabel ?statement ?employer ?employerLabel ?coord ?start ?end ( IF( BOUND( ?start ) && BOUND( ?end ) , ( ( YEAR( ?end ) - YEAR( ?start ) ) * 12 + ( MONTH( ?end ) - MONTH( ?start ) ) - IF( DAY( ?end ) < DAY( ?start ) , 1 , 0 ) ) , "" ) AS ?months ) ( IF( BOUND( ?start ) , YEAR( ?start ) , "" ) AS ?startYear ) ( IF( BOUND( ?end ) , YEAR( ?end ) , "" ) AS ?endYear ) WHERE {
  ?person p:P39 ?statement .
  ?statement ps:P39 wd:Q3809586 .
  OPTIONAL {
    ?statement pq:P108 ?employer .
  }
  OPTIONAL {
    ?statement pq:P580 ?start .
  }
  OPTIONAL {
    ?statement pq:P582 ?end .
  }
  OPTIONAL {
    ?employer wdt:P625 ?coord .
  }
  OPTIONAL {
    ?person rdfs:label ?personLabel FILTER ( LANG( ?personLabel ) = "en" )
  }
  OPTIONAL {
    ?employer rdfs:label ?employerLabel FILTER ( LANG( ?employerLabel ) = "en" )
  }
}
ORDER BY ?personLabel ?start
LIMIT 2000

Summary of approach and results:

1) What I looked for and why
- I identified the Wikidata item for the position "Wikimedian in residence" (wd:Q3809586).
- Relevant qualifiers on P39 statements include employer (pq:P108), start time (pq:P580) and end time (pq:P582); employer items may have coordinates (P625).

2) Query structure
- The final query returns one row per P39 statement where the position is Q3809586. For each row it returns:
  - ?person (IRI) and ?personLabel (English label)
  - ?statement (the statement node on the person’s P39 statement, so multiple residencies per person are distinct)
  - ?employer (IRI) and ?employerLabel (English label) if present (pq:P108)
  - ?coord (employer coordinate, wdt:P625) if the employer item has P625
  - ?start and ?end (the pq:P580 and pq:P582 qualifiers)
  - ?startYear and ?endYear (extracted years)
  - ?months: the tenure length in months computed in SPARQL when both start and end are present

3) Execution
- I executed the query against Wikidata. It returned many rows (the endpoint returned up to the LIMIT of 2000 rows). The query produces actual entity IRIs for persons and employers so you can follow the IRIs for more details.

4) Example rows (as returned by the query)
- Kime Rilla (wd:Q117224803)
  - employer: Research Institute of World’s Ancient/Traditional Cultures and Heritage (wd:Q111085414)
  - start: 2022-03-01, end: 2023-01-01, months: 10, startYear: 2022, endYear: 2023

- Lane Rasberry (wd:Q26202725)
  - This person has many P39 statements for Wikimedian in residence with many employers (town halls and other local organizations). In many of those statements the employer is present but start/end qualifiers are not always provided. Employer items often have coordinates (P625).

Notes and usage tips
- The query returns many rows because some persons have multiple separate residencies (one statement per residency / per employer). Use the ?statement IRI to distinguish multiple residencies for the same person.
- If you want a compact list (one row per person showing only the most recent residency or aggregated data), I can modify the query accordingly.
- If you want CSV/TSV output, run the same SPARQL on the Wikidata endpoint or a SPARQL client and export the results.

If you want, I can:
- Return the full result set here (note: it may be large),
- Restrict to current/ongoing residencies (no pq:P582),
- Aggregate by person, or
- Filter by time range or specific employers.

Final SPARQL query (repeat):

SELECT DISTINCT ?person ?personLabel ?statement ?employer ?employerLabel ?coord ?start ?end (IF(BOUND(?start) && BOUND(?end), ((YEAR(?end)-YEAR(?start))*12 + (MONTH(?end)-MONTH(?start)) - IF(DAY(?end) < DAY(?start), 1, 0)), "") AS ?months) (IF(BOUND(?start), YEAR(?start), "") AS ?startYear) (IF(BOUND(?end), YEAR(?end), "") AS ?endYear) WHERE {
  ?person p:P39 ?statement.
  ?statement ps:P39 wd:Q3809586.
  OPTIONAL { ?statement pq:P108 ?employer. }
  OPTIONAL { ?statement pq:P580 ?start. }
  OPTIONAL { ?statement pq:P582 ?end. }
  OPTIONAL { ?employer wdt:P625 ?coord. }
  OPTIONAL { ?person rdfs:label ?personLabel FILTER(LANG(?personLabel) = "en") }
  OPTIONAL { ?employer rdfs:label ?employerLabel FILTER(LANG(?employerLabel) = "en") }
} ORDER BY ?personLabel ?start
LIMIT 2000

Would you like me to (A) return the full result set here, (B) filter to current residencies only, or (C) produce a compact/aggregated view?

Who are the Wikimedians in residence, and their employers (if available), items (if available), coordinates (if available), end years (if available), start years (if available), and lengths of tenure (in months) (if available)?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Who are the Wikimedians in residence, and their employers (if available), items (if available), coordinates (if available), end years (if available), start years (if available), and lengths of tenure (in months) (if available)?

[Assistant] Step 1: I'll search for the Wikidata item for "Wikimedian in residence" and related properties like position held (P39), employer (P108), start time (P580), end time (P582), and coordinate location (P625). I'll start by searching for the item "Wikimedian in residence".

[Tool]
Top 10 entity alternatives:
1. Wikimedian in residence, also known as Wikipedian Developer in Residence, Wikipedia Outreach Ambassador, Wikipedian in Academy, Wikipedian in Residence, WiR (wd:Q3809586)
2. Wikimedians in Residence Exchange Network, also known as Wikimedians in Residence Exchange Network User Group, WREN (wd:Q63214641): instance of professional association, instance of Wikimedia user group, Wikimedia user group
3. Wikimedian in Residence: Expandi... Visibility and Knowledge Access (wd:Q130502333): program event at WikiConference North America 2024, instance of conference presentation
4. artist-in-residence, also known as residency, Author-in-residence, artist-in-residence program, composer in residence, Workspace Artist Residency (wd:Q713223)
5. Residence Inn by Marriott, also known as Residence Inn (wd:Q7315394): extended-stay all-suite hotel chain run by Marriott International, instance of business
6. Entrepreneur in residence, also known as EIR (wd:Q5380743): organizational position, instance of position
7. Diplomats in Residence, also known as DIRs (wd:Q28405424): instance of diplomat, instance of position
8. Kalichstein-Laredo-Robinson trio, also known as Ensemble in Residence (wd:Q16851425): instance of musical ensemble, US musical ensemble
9. Notes from the Field: Three Wikimedian in Residence Case Studies (wd:Q108545623): chapter from 'Wikipedia and Academic Libraries: A Global Project' published in 2021, instance of chapter
10. Thinker in Residence (wd:Q7784560): South Australian government program, instance of government program

[Assistant] I'll query the qualifiers used on P39 statements where the position is Wikimedian in residence (Q3809586) to see which qualifiers (start time, end time, employer, location, etc.) are actually used.

[Tool]
Got 6 rows and 1 column:
| qual                  |
| --------------------- |
| employer (pq:P108)    |
| start time (pq:P580)  |
| end time (pq:P582)    |
| has cause (pq:P828)   |
| start time (pqv:P580) |
| end time (pqv:P582)   |

[Assistant] I'll query Wikidata for people with the position "Wikimedian in residence" (Q3809586), retrieving for each the employer (pq:P108), start and end times (pq:P580 / pq:P582), and the employer's coordinate location (wdt:P625). I'll also fetch English labels for persons and employers. I'll run a preliminary query to see results.

[Tool]
Got 200 rows and 8 columns, showing the first 5 and last 5 rows below:
| person                       | personLabel        | s                                                | employer                            | employerLabel                 | start | end | coord                                        |
| ---------------------------- | ------------------ | ------------------------------------------------ | ----------------------------------- | ----------------------------- | ----- | --- | -------------------------------------------- |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290 | wd:L1380524                         |                               |       |     | POINT(120.929931 23.969647) (geo:wktLiteral) |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290 | wd:L1380562                         |                               |       |     | POINT(120.969200 23.963561) (geo:wktLiteral) |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290 | spatial reference system (wd:P3037) | spatial reference system (en) |       |     | POINT(10.261996 52.742848) (geo:wktLiteral)  |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290 | Boston (wd:Q100)                    | Boston (en)                   |       |     | POINT(-71.057778 42.360278) (geo:wktLiteral) |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290 | Gabon (wd:Q1000)                    | Gabon (en)                    |       |     | POINT(11.500000 -0.683331) (geo:wktLiteral)  |
| ...                          | ...                | ...                                              | ...                                 | ...                           | ...   | ... | ...                                          |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290 | Nędza (wd:Q1000146)                 | Nędza (en)                    |       |     | POINT(18.313055 50.160556) (geo:wktLiteral)  |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290 | Nędza (wd:Q1000146)                 | Nędza (en)                    |       |     | POINT(18.311030 50.161120) (geo:wktLiteral)  |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290 | Tworóg (wd:Q1000147)                | Tworóg (en)                   |       |     | POINT(18.715555 50.530833) (geo:wktLiteral)  |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290 | Eaton (wd:Q1000148)                 | Eaton (en)                    |       |     | POINT(-84.633900 39.747500) (geo:wktLiteral) |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290 | 2009–10 Tour de Ski (wd:Q1000149)   | 2009–10 Tour de Ski (en)      |       |     | POINT(10.733300 50.700000) (geo:wktLiteral)  |

[Assistant] Now I'll run a SPARQL query that retrieves all people with the position "Wikimedian in residence" (Q3809586), their P39 statement node, employer qualifier (pq:P108), start (pq:P580) and end (pq:P582) qualifiers, employer coordinates (wdt:P625), English labels, and a computed length of tenure in months (when both start and end are available). I'll compute months as (YEAR(end)-YEAR(start))*12 + (MONTH(end)-MONTH(start)) - (1 if DAY(end) < DAY(start) else 0).

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out.

[Assistant]
I'll run a SPARQL query that finds all Wikidata statements where the person held the position "Wikimedian in residence" (Q3809586). For each such statement I'll return:
- the person (IRI) and English label,
- the statement node (so we can distinguish multiple residencies per person),
- the employer (IRI) and English label (if given as a qualifier pq:P108),
- the employer coordinates (wdt:P625) if available,
- start and end dates (pq:P580 / pq:P582),
- start and end years (extracted),
- and a computed length of tenure in months where both start and end are available.

I'll execute the query now (with a reasonable LIMIT to avoid timeouts).

[Tool]
Got 1,000 rows and 11 columns, showing the first 5 and last 5 columns and the first 5 and last 5 rows below:
| person                       | personLabel        | s                                                 | employer                                                                            | employerLabel                                                            | ... | start                               | end                                 | months       | startYear      | endYear        |
| ---------------------------- | ------------------ | ------------------------------------------------- | ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ | --- | ----------------------------------- | ----------------------------------- | ------------ | -------------- | -------------- |
| Kime Rilla (wd:Q117224803)   | Kime Rilla (en)    | s:Q117224803-229342cd-49ea-998b-eabb-bb4cc57356f2 | Research Institute of World’s An...Traditions Cultures and Heritage (wd:Q111085414) | Research Institute of World’s An...Traditions Cultures and Heritage (en) | ... | 2022-03-01T00:00:00Z (xsd:dateTime) | 2023-01-01T00:00:00Z (xsd:dateTime) | 10 (xsd:int) | 2022 (xsd:int) | 2023 (xsd:int) |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Propiac (wd:Q119322962)                                                | town hall of Propiac (en)                                                | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Proyart (wd:Q119322985)                                                | town hall of Proyart (en)                                                | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Propières (wd:Q119322963)                                              | town hall of Propières (en)                                              | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Propriano (wd:Q119322964)                                              | town hall of Propriano (en)                                              | ... |                                     |                                     |              |                |                |
| ...                          | ...                | ...                                               | ...                                                                                | ...                                                                      | ... | ...                                 | ...                                 | ...          | ...            | ...            |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Richemont (wd:Q119323866)                                              | town hall of Richemont (en)                                              | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Richerenches (wd:Q119323867)                                           | town hall of Richerenches (en)                                           | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Richeval (wd:Q119323868)                                               | town hall of Richeval (en)                                               | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Richeville (wd:Q119323869)                                             | town hall of Richeville (en)                                             | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Richtolsheim (wd:Q119323870)                                           | town hall of Richtolsheim (en)                                           | ... |                                     |                                     |              |                |                |

[Assistant]
I'll run a final refined SPARQL query that returns one row per Wikimedian-in-residence statement, including:
- person (IRI) and English label,
- statement node (so different residencies are distinct),
- employer (IRI) and English label (if present),
- employer coordinates (P625) if available,
- start and end datetimes (pq:P580 / pq:P582),
- start and end years,
- tenure length in months (computed in SPARQL when both start and end are present).

I'll execute it now.

[Tool]
Got 2,000 rows and 11 columns, showing the first 5 and last 5 columns and the first 5 and last 5 rows below:
| person                       | personLabel        | statement                                         | employer                                                                            | employerLabel                                                            | ... | start                               | end                                 | months       | startYear      | endYear        |
| ---------------------------- | ------------------ | ------------------------------------------------- | ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ | --- | ----------------------------------- | ----------------------------------- | ------------ | -------------- | -------------- |
| Kime Rilla (wd:Q117224803)   | Kime Rilla (en)    | s:Q117224803-229342cd-49ea-998b-eabb-bb4cc57356f2 | Research Institute of World’s An...Traditions Cultures and Heritage (wd:Q111085414) | Research Institute of World’s An...Traditions Cultures and Heritage (en) | ... | 2022-03-01T00:00:00Z (xsd:dateTime) | 2023-01-01T00:00:00Z (xsd:dateTime) | 10 (xsd:int) | 2022 (xsd:int) | 2023 (xsd:int) |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Propiac (wd:Q119322962)                                                | town hall of Propiac (en)                                                | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Proyart (wd:Q119322985)                                                | town hall of Proyart (en)                                                | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Propières (wd:Q119322963)                                              | town hall of Propières (en)                                              | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Propriano (wd:Q119322964)                                              | town hall of Propriano (en)                                              | ... |                                     |                                     |              |                |                |
| ...                          | ...                | ...                                               | ...                                                                                | ...                                                                      | ... | ...                                 | ...                                 | ...          | ...            | ...            |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Pannecières (wd:Q119321184)                                            | town hall of Pannecières (en)                                            | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Pannes (wd:Q119321185)                                                 | town hall of Pannes (en)                                                 | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Pannes (wd:Q119321187)                                                 | town hall of Pannes (en)                                                 | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Pannessières (wd:Q119321188)                                           | town hall of Pannessières (en)                                           | ... |                                     |                                     |              |                |                |
| Lane Rasberry (wd:Q26202725) | Lane Rasberry (en) | s:Q26202725-B6FA63FC-8172-4F2C-90A3-6B1B61A6B290  | town hall of Panon (wd:Q119321189)                                                  | town hall of Panon (en)                                                  | ... |                                     |                                     |              |                |                |

[Assistant] I will return the final SPARQL query I used and a brief summary of the results (including a couple of example rows returned). The SPARQL query returns one row per Wikimedian-in-residence statement and includes: person IRI and English label, the statement node, employer IRI and English label (if present), the employer coordinates (P625) if available, start and end datetimes (pq:P580 / pq:P582), start and end years, and the computed tenure length in months (when both start and end are present).

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ?player ?playerLabel ?fideID WHERE {
  ?player wdt:P31 wd:Q5 ; wdt:P106 wd:Q10873124 ; wdt:P1440 ?fideID .
  FILTER NOT EXISTS {
    ?player p:P1087 ?eloStmt .
    ?eloStmt ps:P1087 ?eloValue .
    ?eloStmt pq:P585 ?time .
    FILTER ( ?time >= "2012-01-01T00:00:00Z" ^^ xsd:dateTime && ?time < "2012-02-01T00:00:00Z" ^^ xsd:dateTime )
  }
  OPTIONAL {
    ?player rdfs:label ?playerLabel FILTER ( LANG( ?playerLabel ) = "en" )
  }
}
LIMIT 500

Got 500 rows and 3 columns, showing the first 5 and last 5 rows below:
| player                                         | playerLabel                         | fideID   |
| ---------------------------------------------- | ----------------------------------- | -------- |
| Naomi Bashkansky (wd:Q100194836)               | Naomi Bashkansky (en)               | 2072289  |
| Sira Jallow (wd:Q100605576)                    | Sira Jallow (en)                    | 21100535 |
| Vladimir Arseniev (wd:Q101246152)              | Vladimir Arseniev (en)              | 4105800  |
| Yury Pavlovichev (wd:Q101530051)               | Yury Pavlovichev (en)               | 34161322 |
| Viliam Voloshin (wd:Q101780469)                | Viliam Voloshin (en)                | 4104684  |
| ...                                            | ...                                 | ...      |
| Gulcan Sena Kayis (wd:Q108445358)              | Gulcan Sena Kayis (en)              | 34553045 |
| Rianne Ke (wd:Q108445381)                      | Rianne Ke (en)                      | 30908140 |
| Adam Kelly (wd:Q108445445)                     | Adam Kelly (en)                     | 3221911  |
| Elias Keso (wd:Q108445817)                     | Elias Keso (en)                     | 514942   |
| Mariana Sawae Kikuchi Cadilhac (wd:Q108446942) | Mariana Sawae Kikuchi Cadilhac (en) | 2144433  |

I ran the query which returns chess players (Wikidata items) who have a FIDE player ID (property P1440) but do not have an Elo rating (property P1087) statement with a point in time (P585) in January 2012 (2012-01-01 through 2012-01-31). The query returned multiple results (500 rows shown; there may be more). Sample results include: Naomi Bashkansky (wd:Q100194836) - FIDE ID 2072289; Sira Jallow (wd:Q100605576) - FIDE ID 21100535; Vladimir Arseniev (wd:Q101246152) - FIDE ID 4105800; Yury Pavlovichev (wd:Q101530051) - FIDE ID 34161322; Viliam Voloshin (wd:Q101780469) - FIDE ID 4104684, etc. The full SPARQL query is provided above and returns the item IRIs, their English labels (when available), and their FIDE IDs.

Which chess players have a FIDE player ID but do not have an Elo rating recorded for January 2012?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Which chess players have a FIDE player ID but do not have an Elo rating recorded for January 2012?

[Assistant] Step 1: Identify relevant properties and entities. I will search for the property that corresponds to a FIDE player ID and the property for Elo rating (including time-specific statements for January 2012). I'll start by searching for properties related to "FIDE" and "Elo". I will run property searches on the Wikidata KG.

[Tool]
Top 10 property alternatives:
1. FIDE player ID, also known as FIDE.com player ID, FIDE ID (wd:P1440 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier on the FIDE database for chess players
2. OlimpBase FIDE ratings ID (wd:P11967 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): Elo rating ID on OlimpBase
3. Chessgames.com player ID, also known as ChessGames.com ID, Chess Games ID, ChessGames ID (wd:P1665 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier on the website Chessgames.com
4. Chess.com player ID, also known as Chess.com player identifier (wd:P11065 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for a chess player on Chess.com
5. Israel Chess Federation player ID, also known as ICF ID (wd:P3867 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for a chess player from the Israel Chess Federation
6. USCF player ID, also known as USCF ID, US Chess Federation ID, US Chess Federation player ID (wd:P3558 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for a chess player issued by the US Chess Federation
7. Chess Federation of Canada ID (wd:P11094 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): chess player's page on the website of the Canadian Chess Federation
8. Lichess username, also known as lichess id (wd:P8976 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): username on the chess website lichess.org, subproperty of website username or ID
9. ChessTempo.com player ID, also known as chesstempo.com player ID, Chess Tempo player ID (wd:P3315 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for chess players at ChessTempo.com
10. World Table Tennis player ID, also known as International Table Tennis Federation player ID, ITTF player ID, WTT player ID (wd:P1364 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): 6-digit identifier for a table tennis player at the World Table Tennis (WTT) website

[Tool]
Top 10 property alternatives:
1. Elo rating (wd:P1087 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): quantitative measure of one's game-playing ability, particularly in classical chess
2. review score, also known as rating (score), review rating (wd:P444 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): review score received by a creative work or other entity
3. rating (wd:P4271 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): qualifier to indicate a score given by the referenced source indicating the quality or completeness of the statement
4. number of reviews/ratings, also known as number of ratings, number of reviews, ratings, reviews (wd:P7887 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): qualifier on review score to state the number of user reviews, user ratings or critic reviews
5. dan/kyu rank, also known as go rank, judo rank, kendo rank, renju rank, shogi rank (wd:P468 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): rank system used in several board games (e.g. go, shogi, renju), martial arts (e.g. judo, kendo, wushu) and some other games
6. ranking, also known as peak position, place, placing, position, rank (wd:P1352 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): subject's ordinal position as qualitatively evaluated relative to other members of a group
7. score method, also known as scoring method, scoring system, scoring metric, score type, score system (wd:P1443 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): qualifier of "points/goal scored by (P1363)"
8. series ordinal, also known as unit number, sort order, sorting order, ordinal, series number (wd:P1545 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): position of an item in its parent series (most frequently a 1-ba...d from "ranking" defined as a property for evaluating a quality)
9. military or police rank, also known as police rank, rank, naval rank, military rank (wd:P410 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): military or police rank achieved by a person (should usually hav...ualifier), or military or police rank associated with a position
10. taxon rank, also known as rank, taxonomic rank, type of taxon (wd:P105 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): level in a taxonomic hierarchy, subproperty of instance of

[Assistant] I will search for the Wikidata item for "chess player" to use as an occupation or instance filter.

[Tool]
Top 10 entity alternatives:
1. chess player (wd:Q10873124)
2. The Chess Player, also known as Le joueur d’echecs, Chess Player (wd:Q2551767): 1927 French film directed by Raymond Bernard, instance of film
3. Go Player, also known as Chess Player (wd:Q5093307): 2006 Chinese television series, instance of television series
4. The Chess Player, also known as Chess Player, Le Joueur d'échecs (wd:Q3223641): 1938 film by Jean Dréville, instance of film
5. Chess Player (wd:Q49213741): painting by George Benjamin Luks, instance of painting
6. chess player (wd:L1361125-S1)
7. The Turk, also known as Mechanical Turk, Automaton Chess Player (wd:Q275924): instance of hoax chess automaton, instance of work of art, instance of appliance, chess automaton hoax
8. Maelzel's Chess Player (wd:Q6729212): essay by Edgar Allan Poe, exposing the chess automaton "The Turk" as fraudulent, instance of literary work
9. The Chess Players, also known as chess players (wd:Q25569090): painting by Cornelis de Man, instance of painting
10. Chess Players (wd:Q25395333): painting in the manner of Caravaggio, instance of painting

[Assistant] I'll verify the property for "point in time" (used as a qualifier for dated Elo ratings), then I'll run a SPARQL query that finds humans with occupation "chess player" who have a FIDE player ID (P1440) and for whom there is no Elo rating (P1087) statement qualified with point in time (P585) in January 2012. Now I'll search for the "point in time" property to confirm its identifier.

[Tool]
Top 10 property alternatives:
1. point in time, also known as year, when, time of event, time, during (wd:P585 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
2. valid in period, also known as valid in season, valid for season, valid for period, valid for, time period (wd:P1264 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): time period when a statement is valid
3. set in period, also known as set in, set in era, set in time, setting, significant event (wd:P2408 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): historical, contemporary, or future period, year, century or day...rk or genre is set in or event featured in the story of the work
4. time period, also known as oge (oge akụkọ ihe mere eme ma ọ...ụ mere ma ọ bụ nke ejikọtara ya. (wd:P2348 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): time period (historic period or era, sports season, theatre seas...c.) in which the subject occurred or with which it is associated
5. start time, also known as start date, since, join time, joined, join date (wd:P580 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): time an entity begins to exist or a statement starts being valid, subproperty of point in time
6. date depicted, also known as date shown, depicted date, depicted time, depicts date, shown as at date (wd:P2913 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): date represented in a work (for narrative works use P2408)
7. term length of position, also known as position term, time in position, term of position, term length, length of term (wd:P2097 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): length of time in years (unit: Q577) a person (usually a politician) is to serve in a particular position. Do not add bounds., subproperty of duration
8. history of topic, also known as chronology of subject, timeline of topic, timeline of the topic, timeline of the subject, timeline of subject (wd:P2184 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): item about the historical development of a subject's topic, exam... To list key events of the topic, use "significant event" (P793), subproperty of studied by
9. latest date, also known as terminus ante quem, prior to, on or before this date, no later than, maximum date (wd:P1326 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): latest possible time that something could have occurred. Use as qualifier for other date properties
10. recording date, also known as rec. date, recorded date, record date, recdate, date of recording (wd:P10135 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): the date when a recording was made, subproperty of inception

[Assistant] Plan: construct a SPARQL SELECT query that finds items that are humans and chess players, have FIDE player ID (P1440), and do NOT have an Elo rating (P1087) with point in time in January 2012. To ensure lack of Elo rating for Jan 2012, I'll look for absence of a P1087 statement with qualifier P585 within date range 2012-01-01 to 2012-01-31. Use MINUS or FILTER NOT EXISTS. Also ensure person is instance of human (wd:Q5) and/or occupation chess player (wd:Q10873124). I'll test the query on a small sample. I'll build a query returning the person IRI and maybe labels and the FIDE ID.

[Tool]
Got 100 rows and 3 columns, showing the first 5 and last 5 rows below:
| player                             | playerLabel             | fideID   |
| ---------------------------------- | ----------------------- | -------- |
| Naomi Bashkansky (wd:Q100194836)   | Naomi Bashkansky (en)   | 2072289  |
| Sira Jallow (wd:Q100605576)        | Sira Jallow (en)        | 21100535 |
| Vladimir Arseniev (wd:Q101246152)  | Vladimir Arseniev (en)  | 4105800  |
| Yury Pavlovichev (wd:Q101530051)   | Yury Pavlovichev (en)   | 34161322 |
| Viliam Voloshin (wd:Q101780469)    | Viliam Voloshin (en)    | 4104684  |
| ...                                | ...                     | ...      |
| Gulenay Aydin (wd:Q108305443)      | Gulenay Aydin (en)      | 34557431 |
| Blass Barria (wd:Q108306734)       | Blass Barria (en)       | 6600069  |
| Yannay Ben Ari (wd:Q108307379)     | Yannay Ben Ari (en)     | 2815222  |
| Safin Benyahia (wd:Q108307579)     | Safin Benyahia (en)     | 7905556  |
| Francesco Bettalli (wd:Q108307870) | Francesco Bettalli (en) | 2816453  |

[Assistant] I'll run a refined SPARQL query that finds humans with a FIDE player ID (P1440) and that do not have any Elo rating (P1087) statement whose point in time (P585) falls in January 2012 (2012-01-01 to 2012-01-31). I removed the occupation constraint to avoid missing players who may not have the occupation property set. I'll execute the query to get results.

[Tool]
Got 200 rows and 3 columns, showing the first 5 and last 5 rows below:
| player                            | playerLabel            | fideID   |
| --------------------------------- | ---------------------- | -------- |
| Naomi Bashkansky (wd:Q100194836)  | Naomi Bashkansky (en)  | 2072289  |
| Sira Jallow (wd:Q100605576)       | Sira Jallow (en)       | 21100535 |
| Vladimir Arseniev (wd:Q101246152) | Vladimir Arseniev (en) | 4105800  |
| Yury Pavlovichev (wd:Q101530051)  | Yury Pavlovichev (en)  | 34161322 |
| Viliam Voloshin (wd:Q101780469)   | Viliam Voloshin (en)   | 4104684  |
| ...                               | ...                    | ...      |
| Kata Karacsonyi (wd:Q108335421)   | Kata Karacsonyi (en)   | 769584   |
| Petya Karaivanova (wd:Q108335427) | Petya Karaivanova (en) | 2919150  |
| Sofiia Kasaeva (wd:Q108335600)    | Sofiia Kasaeva (en)    | 34180530 |
| Michelle Katkov (wd:Q108335682)   | Michelle Katkov (en)   | 2816393  |
| Jind Kaur (wd:Q108335723)         | Jind Kaur (en)         | 30933099 |

[Assistant] I'll execute the final SPARQL query (restricting to items with occupation "chess player") to retrieve players (IRIs), English labels and FIDE IDs who do not have an Elo rating recorded with point in time in January 2012. I'll then return the query and the results.

[Tool]
Got 500 rows and 3 columns, showing the first 5 and last 5 rows below:
| player                                         | playerLabel                         | fideID   |
| ---------------------------------------------- | ----------------------------------- | -------- |
| Naomi Bashkansky (wd:Q100194836)               | Naomi Bashkansky (en)               | 2072289  |
| Sira Jallow (wd:Q100605576)                    | Sira Jallow (en)                    | 21100535 |
| Vladimir Arseniev (wd:Q101246152)              | Vladimir Arseniev (en)              | 4105800  |
| Yury Pavlovichev (wd:Q101530051)               | Yury Pavlovichev (en)               | 34161322 |
| Viliam Voloshin (wd:Q101780469)                | Viliam Voloshin (en)                | 4104684  |
| ...                                            | ...                                 | ...      |
| Gulcan Sena Kayis (wd:Q108445358)              | Gulcan Sena Kayis (en)              | 34553045 |
| Rianne Ke (wd:Q108445381)                      | Rianne Ke (en)                      | 30908140 |
| Adam Kelly (wd:Q108445445)                     | Adam Kelly (en)                     | 3221911  |
| Elias Keso (wd:Q108445817)                     | Elias Keso (en)                     | 514942   |
| Mariana Sawae Kikuchi Cadilhac (wd:Q108446942) | Mariana Sawae Kikuchi Cadilhac (en) | 2144433  |

[Assistant] Now I'll finalize by returning the SPARQL query and summarizing the result: this query returns chess players with a FIDE ID but without an Elo rating for January 2012. I'll provide the SPARQL query and mention that the query returns multiple results (500 shown, could be more) and perhaps include a sample of results. I will include the full query as the final answer.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?item ?itemLabel ?coord ?inception ?year ?century WHERE {
  ?item wdt:P131 + wd:Q12549 .
  ?item wdt:P625 ?coord .
  ?item wdt:P571 ?inception .
  BIND( YEAR( ?inception ) AS ?year ) .
  FILTER ( BOUND( ?year ) ) .
  BIND( ROUND( ?year / 100.0 ) AS ?centRounded ) .
  BIND( xsd:integer ( ?centRounded * 100 ) AS ?century ) .
  OPTIONAL {
    ?item rdfs:label ?itemLabel FILTER ( LANG( ?itemLabel ) = "en" )
  }
}
ORDER BY ?century ?itemLabel
LIMIT 1000

I executed the query on Wikidata. There are 2171 items in Ille-et-Vilaine with coordinates and an inception date that yields a year. The provided SPARQL query returns each item's IRI, optional English label, coordinates, inception date, the extracted year, and the century of inception rounded to the nearest century.

What are the items located in Ille-et-Vilaine, along with their coordinates and the century of their inception (rounded to the nearest century)?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What are the items located in Ille-et-Vilaine, along with their coordinates and the century of their inception (rounded to the nearest century)?

[Assistant] Step 1: I'll find the Wikidata item for Ille-et-Vilaine to use in the query. I'll search for the entity by name. Then I'll identify the properties to use: location (P131), coordinates (P625), and inception (P571). I'll verify those properties exist. Now I'll search for Ille-et-Vilaine.

[Tool]
Top 10 entity alternatives:
1. Ille-et-Vilaine (wd:Q12549): instance of department of France, French department
2. conseil de préfecture d'Ille-et-Vilaine, also known as CP 35, CP d'Ille-et-Vilaine, CP Ille-et-Vilaine (wd:Q63048509)
3. Departmental council of Ille-et-Vilaine, also known as Ille-et-Vilaine departmental council, Conseil départemental d'Ille-et-Vilaine (wd:Q23782070): deliberative assembly of the French department of Ille-et-Vilaine since April 2015, instance of departmental council
4. General council of Ille-et-Vilaine, also known as Conseil général d'Ille-et-Vilaine, Ille-et-Vilaine general council (wd:Q2993952): deliberative assembly of the French department of Morbihan before March 2015, instance of General council
5. demographics of Ille-et-Vilaine (wd:Q3043599)
6. economy of Ille-et-Vilaine (wd:Q102129069)
7. Prefecture of Ille-et-Vilaine (wd:Q59210345): instance of organization, French prefecture
8. Prefect of Ille-et-Vilaine (wd:Q62694838)
9. Miss Ille-et-Vilaine 2025 (wd:Q133462623): instance of beauty pageant edition
10. Saint-Méen-le-Grand (Ille-et-Vilaine). Abbatiale (wd:Q107408199): instance of scholarly article, scientific article

[Assistant] Now I'll verify the properties for coordinates and inception exist and their identifiers (P625 and P571). I'll search for them to be sure.

[Tool]
Top 10 property alternatives:
1. coordinates of depicted place, also known as depicted item geolocation, geolocation of object, object geolocation (wd:P9149 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): coordinates of the place depicted in the work (or Commons image)
2. coordinate location, also known as gps co-ordinates, wgs 84, gps coordinates, gps location, latitude (wd:P625 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
3. occupant, also known as location of, tenant, resident, renter, occupiers (wd:P466 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): person or organization occupying property, subproperty of used by
4. this zoological name is coordinate with, also known as coordinate name (wd:P2743 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): links coordinate zoological names, subproperty of different from
5. street address, also known as full address, address, postal address, physical address, mail address (wd:P6375 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): full street address where subject is located. Include building n...t country; use also P669 if the street has its own separate item
6. relative position within image, also known as IIIF syntax relative position, relative position in image, position within image, position in the image, pct relative position (wd:P2677 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): position of a motif within a larger image, defined by  x-offset ...h of the crop region (as a percentage of the whole image) values
7. location, also known as neighborhood, locale, neighbourhood, place, place held (wd:P276 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
8. adjacent building, also known as adjoining building, next to, neighboring building, located next to (wd:P3032 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): building adjacent to the item, subproperty of connects with
9. detail map, also known as map (wd:P1621 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): map containing details about the entire location, subproperty of locator map image
10. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): the place where the person is or has been, resident, subproperty of location

[Tool]
Top 10 property alternatives:
1. inception, also known as inception date, founding date, founded in, founded on date, founded on (wd:P571 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): time when an entity begins to exist; for date of official opening use P1619, subproperty of start time
2. AI-generation prompt, also known as AI-generated media prompt, AI prompt, artificial intelligence-generated media prompt, prompt used to generate AI work (wd:P13381 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): exact prompt that was used to generate this AI-generated media or work
3. image of entrance, also known as door image, image of entry, image of entrance, image of access point, gate image (wd:P9721 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): view of an entry point of an architectural structure, vehicle, t... space, in the entering direction (not in the exiting direction), subproperty of image
4. programmed in, also known as language, programming language, written in (wd:P277 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): the programming language(s) in which the software is developed
5. aperture (wd:P7863 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): aperture of a camera lens
6. announcement date, also known as date teased, made public on, public announcement date, published, released (wd:P6949 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): time of the first public presentation of a subject by the creator, of information by the media, subproperty of point in time
7. fabrication method, also known as process used, preparation method, obtained by, method used, method of preparation (wd:P2079 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): method, process or technique used to grow, cook, weave, build, assemble, manufacture the item, subproperty of uses
8. demo of, also known as demo version of, game demo of, trial version of (wd:P12050 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): video game or software that this trial version is based on
9. digital representation of, also known as digitized copy of, scanned copy of, faithful two-dimensional representation of, faithful reproduction of, faithful representation of (wd:P6243 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): faithful digitized representation of the indicated object or work. For use on Commons MediaInfo entities., subproperty of depicts
10. X-SAMPA code, also known as phoneme in X-SAMPA, X-SAMPA, XSAMPA (wd:P2859 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): Extended Speech Assessment Methods Phonetic Alphabet (X-SAMPA) code for phoneme

[Assistant]
I will construct a SPARQL query that finds items located in Ille-et-Vilaine (wd:Q12549) via P131 (located in the administrative territorial entity) or possibly P17? The typical property is P131. I'll get items with coordinates (P625) and inception (P571). I need to compute century of inception rounded to nearest century. SPARQL can extract year and then compute rounding. QLever supports math functions? We have math prefix. But rule 6 said computations must be in SPARQL. We'll use xsd:integer and math:round? There's a math prefix in prefixes: math: <http://www.w3.org/2005/xpath-functions/math#>. In QLever, functions.qlever maybe supported. Use expression: ?year = YEAR(?inception). YEAR() function exists? Standard SPARQL has YEAR(). Use BIND( year(xsd:dateTime(?inception)) as ?year). Then compute century: century = ROUND(?year / 100) * 100? But rounding to nearest century means e.g., year 1701 -> 1700? Wait rounding to nearest century: For year 1701, divide by 100 = 17.01 round = 17 -> *100 =1700. For year 1750 -> 17.5 rounding -> 18 -> 1800. For year 1800 -> 18.0 round 18 -> 1800. So formula: BIND( xsd:double(?year) / 100 as ?centD) BIND( math:round(?centD) as ?centRounded ) BIND( xsd:integer(?centRounded * 100) as ?century). But math:round maybe math:round(?x) returns integer? Need to check QLever supports math:round. The prefixes include math. SPARQL allows functions from XPath? QLever may support math:round. Let's attempt.

Also must ensure we only include items with inception date values. Inception can be date-time with precision; some items have qualifiers. Use wdt:P571 and wdt:P625 for direct. Locate items where ?item wdt:P131 wd:Q12549. But some items may be in nested locations: located in the administrative territorial entity could be deeper; but user asked "located in Ille-et-Vilaine" — likely direct P131 equals that. Could also include items with P131 chain where administrative territory is within Ille-et-Vilaine. But simplest: include items where P131 is Ille-et-Vilaine or located in any place whose administrative entity is Ille-et-Vilaine? The instruction 5 said don't stop early; but keep refining. Perhaps include items that are located in administrative entity equal to Ille-et-Vilaine (wdt:P131/wdt:P131*? SPARQL property paths can be used: ?item wdt:P131+ wd:Q12549 to traverse P131 chains. Use wdt:P131+ path to include items whose P131 chain leads to Ille-et-Vilaine. Good.

Also ensure items have coordinates and inception. Query will return ?item ?coords ?inception ?year ?century and optionally labels. Use rdfs:label with FILTER(LANG(...)). But rule 4: return identifiers/IRIs and labels optional using optional clauses. So include rdfs:label optional.

We must execute intermediate queries per steps. The developer instructions require explaining thought process before and after each step and function call. So I must narrate. Also must not use SERVICE wikibase:label. Use rdfs:label.

Now proceed to construct initial query to get items in Ille-et-Vilaine with coords and inception, limit maybe. But need to execute final query and ensure returns results. Let's craft query:

SELECT ?item ?itemLabel ?coord ?inception ?year ?century WHERE {
  ?item wdt:P131+ wd:Q12549.
  ?item wdt:P625 ?coord.
  ?item wdt:P571 ?inception.
  BIND(year(xsd:dateTime(?inception)) as ?year)
  BIND(xsd:double(?year)/100 as ?centD)
  BIND(math:round(?centD) as ?centRounded)
  BIND(xsd:integer(?centRounded*100) as ?century)
  OPTIONAL { ?item rdfs:label ?itemLabel FILTER(LANG(?itemLabel) = "en") }
}

But math:round returns maybe xsd:integer; multiply by 100 needs arithmetic: (?centRounded * 100) allowed.

QLever might not accept math:round; alternative use function round(?centD) — standard SPARQL 1.1 has ROUND() numeric function. Yes SPARQL has ROUND(). So use ROUND(?centD). Good. Use BIND(ROUND(?centD) AS ?centRounded). So use standard ROUND.

Also YEAR() function exists in SPARQL 1.1: YEAR(?inception) returns integer. So BIND(YEAR(?inception) AS ?year). That is simpler. But inception may contain only year; YEAR handles. So final BINDs:

BIND(YEAR(?inception) AS ?year)
BIND(ROUND(?year/100.0) AS ?centRounded)
BIND((?centRounded*100) AS ?century)

But multiplication of numeric: SPARQL allows ?centRounded * 100. Might need xsd:integer conversion: BIND(xsd:integer(?centRounded*100) AS ?century)

Also RETURN coords: wdt:P625 returns geoshape? It's literal with "Point(long lat)". So variable ?coord typed as geo etc. It's fine.

Add ORDER BY ?century ?itemLabel. The developer rules: must execute final query before answering. We'll run execute.

First explain step and call execute. So per instructions, before calling execute, must explain thought process. I have explained earlier; need to before function call again maybe. The additional rules require explaining before and after each step and function call. We've explained previously but must maintain for each call.

Now call functions.execute with the query.
I'll run a SPARQL query that finds items whose administrative-entity chain (P131+) leads to Ille-et-Vilaine (wd:Q12549), with coordinates (wdt:P625) and inception date (wdt:P571). I'll compute the inception year with YEAR() and round to the nearest century using ROUND(year/100) * 100. I'll request English labels if available. Now I'll execute the query.

[Tool]
Got 1,000 rows and 6 columns, showing the first 5 and last 5 rows below:
| item                                  | itemLabel                   | coord                                       | inception                            | year            | century         |
| ------------------------------------- | --------------------------- | ------------------------------------------- | ------------------------------------ | --------------- | --------------- |
| wd:Q29301440                          |                             | POINT(-1.645117 48.112356) (geo:wktLiteral) | _:bn398823                           |                 |                 |
| Moulin de Gailieu (wd:Q29459208)      | Moulin de Gailieu (en)      | POINT(-1.747440 47.926509) (geo:wktLiteral) | _:bn952092                           |                 |                 |
| Moulin de La Bouëxière (wd:Q29447258) | Moulin de La Bouëxière (en) | POINT(-1.751504 47.945815) (geo:wktLiteral) | _:bn263606                           |                 |                 |
| Menhir de La Nouette (wd:Q97162019)   | Menhir de La Nouette (en)   | POINT(-1.931290 48.132430) (geo:wktLiteral) | -5000-01-01T00:00:00Z (xsd:dateTime) | -5000 (xsd:int) | -5000 (xsd:int) |
| Pierre de Richebourg (wd:Q22991024)   | Pierre de Richebourg (en)   | POINT(-1.323080 47.882535) (geo:wktLiteral) | -5000-01-01T00:00:00Z (xsd:dateTime) | -5000 (xsd:int) | -5000 (xsd:int) |
| ...                                   | ...                         | ...                                         | ...                                  | ...             | ...             |
| wd:Q120214316                         |                             | POINT(-1.784573 48.248779) (geo:wktLiteral) | 2010-01-01T00:00:00Z (xsd:dateTime)  | 2010 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214322                         |                             | POINT(-1.783700 48.248250) (geo:wktLiteral) | 2001-01-01T00:00:00Z (xsd:dateTime)  | 2001 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214326                         |                             | POINT(-1.782420 48.248080) (geo:wktLiteral) | 2004-01-01T00:00:00Z (xsd:dateTime)  | 2004 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214327                         |                             | POINT(-1.782420 48.248080) (geo:wktLiteral) | 2004-01-01T00:00:00Z (xsd:dateTime)  | 2004 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214333                         |                             | POINT(-1.781384 48.165265) (geo:wktLiteral) | 2013-01-01T00:00:00Z (xsd:dateTime)  | 2013 (xsd:int)  | 2000 (xsd:int)  |

[Assistant] I will refine the query to exclude non-literal inception values (which prevented YEAR() from producing a value for some rows). I'll add FILTER(isLiteral(?inception)). Then I'll execute the refined query.

[Tool] Got no rows and 6 columns

[Assistant] I'll run a small diagnostic query to inspect the nature (literal or not) and datatype of the inception values for items in Ille-et-Vilaine.

[Tool]
Got 50 rows and 5 columns, showing the first 5 and last 5 rows below:
| item                                         | itemLabel                         | inception                           | isLit               | dtype        |
| -------------------------------------------- | --------------------------------- | ----------------------------------- | ------------------- | ------------ |
| La Femme entre les deux âges (wd:Q101499958) | La Femme entre les deux âges (en) | 1575-01-01T00:00:00Z (xsd:dateTime) | false (xsd:boolean) | xsd:dateTime |
| La Femme entre les deux âges (wd:Q101499958) | La Femme entre les deux âges (en) | 1590-01-01T00:00:00Z (xsd:dateTime) | false (xsd:boolean) | xsd:dateTime |
| Noyal-Châtillon-sur-Seiche (wd:Q1021786)     | Noyal-Châtillon-sur-Seiche (en)   | 1993-01-01T00:00:00Z (xsd:dateTime) | false (xsd:boolean) | xsd:dateTime |
| Nantes-Brest canal (wd:Q1032581)             | Nantes-Brest canal (en)           | 1803-01-01T00:00:00Z (xsd:dateTime) | false (xsd:boolean) | xsd:dateTime |
| maison Odorico (wd:Q103762645)               | maison Odorico (en)               | 1940-01-01T00:00:00Z (xsd:dateTime) | false (xsd:boolean) | xsd:dateTime |
| ...                                          | ...                               | ...                                 | ...                 | ...          |
| wd:Q112056834                                |                                   | 1759-01-01T00:00:00Z (xsd:dateTime) | false (xsd:boolean) | xsd:dateTime |
| Roazhon Park (wd:Q1121760)                   | Roazhon Park (en)                 | 1912-09-15T00:00:00Z (xsd:dateTime) | false (xsd:boolean) | xsd:dateTime |
| The reverie (wd:Q112294875)                  | The reverie (en)                  | 1855-01-01T00:00:00Z (xsd:dateTime) | false (xsd:boolean) | xsd:dateTime |
| wd:Q112984181                                |                                   | 2014-12-03T00:00:00Z (xsd:dateTime) | false (xsd:boolean) | xsd:dateTime |
| wd:Q113253792                                |                                   | 1825-01-01T00:00:00Z (xsd:dateTime) | false (xsd:boolean) | xsd:dateTime |

[Assistant] I'll try using the statement path p:P571 / ps:P571 to get literal inception date values (instead of wdt:P571), and then compute the year and rounded century. I'll query items with P131+ to Ille-et-Vilaine, coordinates (wdt:P625), and ps:P571 inception values. Then I'll execute the query.

[Tool]
Got 1,000 rows and 6 columns, showing the first 5 and last 5 rows below:
| item                                      | itemLabel                        | coord                                       | inception                            | year            | century         |
| ----------------------------------------- | -------------------------------- | ------------------------------------------- | ------------------------------------ | --------------- | --------------- |
| wd:Q29301440                              |                                  | POINT(-1.645117 48.112356) (geo:wktLiteral) | _:bn53218                            |                 |                 |
| Moulin de Gailieu (wd:Q29459208)          | Moulin de Gailieu (en)           | POINT(-1.747440 47.926509) (geo:wktLiteral) | _:bn174880                           |                 |                 |
| Moulin de La Bouëxière (wd:Q29447258)     | Moulin de La Bouëxière (en)      | POINT(-1.751504 47.945815) (geo:wktLiteral) | _:bn1145021                          |                 |                 |
| Saint-Georges swimming pool (wd:Q3389224) | Saint-Georges swimming pool (en) | POINT(-1.674500 48.112200) (geo:wktLiteral) | _:bn1022346                          |                 |                 |
| Menhir de La Nouette (wd:Q97162019)       | Menhir de La Nouette (en)        | POINT(-1.931290 48.132430) (geo:wktLiteral) | -5000-01-01T00:00:00Z (xsd:dateTime) | -5000 (xsd:int) | -5000 (xsd:int) |
| ...                                       | ...                              | ...                                         | ...                                  | ...             | ...             |
| wd:Q120214322                             |                                  | POINT(-1.783700 48.248250) (geo:wktLiteral) | 2001-01-01T00:00:00Z (xsd:dateTime)  | 2001 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214276                             |                                  | POINT(-1.793610 48.055200) (geo:wktLiteral) | 1995-01-01T00:00:00Z (xsd:dateTime)  | 1995 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214278                             |                                  | POINT(-1.793035 47.963897) (geo:wktLiteral) | 2010-01-01T00:00:00Z (xsd:dateTime)  | 2010 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214284                             |                                  | POINT(-1.791100 47.962910) (geo:wktLiteral) | 1987-01-01T00:00:00Z (xsd:dateTime)  | 1987 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214296                             |                                  | POINT(-1.789260 48.056500) (geo:wktLiteral) | 1980-01-01T00:00:00Z (xsd:dateTime)  | 1980 (xsd:int)  | 2000 (xsd:int)  |

[Assistant] The results show many rows, but some inception values are blank because some ps:P571 statements have blank node values (maybe date ranges or unknown). To ensure we only get literal dates, I'll add FILTER(isLiteral(?inception)). I'll re-run the query.

[Tool] Got no rows and 6 columns

[Assistant] I'll run a query using wdt:P571 but filter to keep only rows where YEAR(?inception) produced a binding, i.e., year is bound. This should exclude the blank/unknown values. Then I'll compute the rounded century.

[Tool]
Got 1,000 rows and 6 columns, showing the first 5 and last 5 rows below:
| item                                                                | itemLabel                                                 | coord                                       | inception                            | year            | century         |
| ------------------------------------------------------------------- | --------------------------------------------------------- | ------------------------------------------- | ------------------------------------ | --------------- | --------------- |
| Menhir de La Nouette (wd:Q97162019)                                 | Menhir de La Nouette (en)                                 | POINT(-1.931290 48.132430) (geo:wktLiteral) | -5000-01-01T00:00:00Z (xsd:dateTime) | -5000 (xsd:int) | -5000 (xsd:int) |
| Pierre de Richebourg (wd:Q22991024)                                 | Pierre de Richebourg (en)                                 | POINT(-1.323080 47.882535) (geo:wktLiteral) | -5000-01-01T00:00:00Z (xsd:dateTime) | -5000 (xsd:int) | -5000 (xsd:int) |
| La Roche Longue (wd:Q22991619)                                      | La Roche Longue (en)                                      | POINT(-1.629056 48.586972) (geo:wktLiteral) | -4000-01-01T00:00:00Z (xsd:dateTime) | -4000 (xsd:int) | -4000 (xsd:int) |
| Retranchement de l'âge du Fer de la pointe du Meinga (wd:Q22991044) | Retranchement de l'âge du Fer de la pointe du Meinga (en) | POINT(-1.935911 48.697058) (geo:wktLiteral) | -1000-01-01T00:00:00Z (xsd:dateTime) | -1000 (xsd:int) | -1000 (xsd:int) |
| Archaeological site of la Bouexière (wd:Q22976883)                  | Archaeological site of la Bouexière (en)                  | POINT(-1.900603 48.049621) (geo:wktLiteral) | -100-01-01T00:00:00Z (xsd:dateTime)  | -100 (xsd:int)  | -100 (xsd:int)  |
| ...                                                                 | ...                                                       | ...                                         | ...                                  | ...             | ...             |
| wd:Q120214326                                                       |                                                           | POINT(-1.782420 48.248080) (geo:wktLiteral) | 2004-01-01T00:00:00Z (xsd:dateTime)  | 2004 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214327                                                       |                                                           | POINT(-1.782420 48.248080) (geo:wktLiteral) | 2004-01-01T00:00:00Z (xsd:dateTime)  | 2004 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214185                                                       |                                                           | POINT(-1.823810 47.822000) (geo:wktLiteral) | 1998-01-01T00:00:00Z (xsd:dateTime)  | 1998 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214141                                                       |                                                           | POINT(-1.834600 47.721130) (geo:wktLiteral) | 1998-01-01T00:00:00Z (xsd:dateTime)  | 1998 (xsd:int)  | 2000 (xsd:int)  |
| wd:Q120214164                                                       |                                                           | POINT(-1.828606 48.153241) (geo:wktLiteral) | 1995-01-01T00:00:00Z (xsd:dateTime)  | 1995 (xsd:int)  | 2000 (xsd:int)  |

[Assistant] I'll count how many distinct items match the criteria (located in Ille-et-Vilaine via P131+, have coordinates P625 and inception P571 with a valid YEAR) so I can report how many results there are. I'll run a COUNT query.

[Tool]
Got 1 row and 1 column:
| count          |
| -------------- |
| 2171 (xsd:int) |

[Assistant]
There are 2171 matching items. The user asked: "What are the items located in Ille-et-Vilaine, along with their coordinates and the century of their inception (rounded to the nearest century)?"

I will provide the final SPARQL query that returns item IRIs, optional English labels, coordinates, inception date, the extracted year, and the rounded century. According to the rules, the final query must be executed before answering; I have executed it. I'll now present the final query and summarize the answer noting the query returns 2171 items (I will include that count).

[Tool] Stopped generation process